What data for this category looks like
The data for this category primarily comes from the food safety sampling monitoring system, the State Administration for Market Regulation sampling results query system, the laboratory information management system (LIMS) of inspection institutions, and the account books of food producers and operators. The update frequency is monthly. Daily documents include sampling plans, sampling slips, inspection reports, non-compliant food verification and disposal reports, and risk control announcements. Core fields include sampling number, inspection items, non-compliance determination results, disposal measures, and others. Most documents use structured form and standardized report formats. It is necessary to ensure that no fields are missing and formats are unified.
Constraints imposed by these characteristics on HTTP interfaces and external systems
Fixed monthly updated data requires the interface to adapt to batch pull rhythms, to avoid frequent calls exceeding system limits. Structured forms and reports require the interface to support precise verification and format conversion of multiple fields, to ensure that core fields such as sampling slip numbers and inspection results are not missing. Cross-system docking, such as pulling inspection reports from LIMS and synchronizing to the supervision publicity system, requires unified data format conventions, while also being compatible with field differences from different source systems. The sensitive nature of documents related to non-compliance disposal requires adding permission verification to interface transmission, to prevent data leaks and ensure the safety of supervision processes.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Interface timeout period | 300–600 seconds | Sampling-related document data volume is large. A single request requires sufficient time to complete pulling and format conversion, to avoid mid-request interruption |
| Request authentication configuration | Use the Authorization header with a Bearer token | Complies with industry general interface security specifications, adapts to the permission verification rules of supervision systems, and ensures data transmission security |
| Batch pull quantity | First 100 entries | Monthly updated data volume is moderate. Pulling too many entries at one time increases system load, while pulling too few increases the number of calls |
| Response data processing | Extract core content via the responseData field | Adapts to FastGPT's response parsing logic, facilitating subsequent structured processing of documents such as inspection reports and sampling slips |
| Request variable configuration | Pass dynamic parameters via variables | Adapts to dynamically generated parameters such as sampling slip numbers and inspection batches, improving interface call flexibility |
| Call frequency limit | No more than 20 times per minute | Adapts to the interface current limiting rules of most supervision systems, avoiding triggering interception that causes call failures |
Three common configuration mistakes
- Issue: The request body content in the HTTP request module cannot be edited or saved normally. Cause: The request body format is not selected correctly, or there is a form rendering exception in the deployed version, resulting in configuration that cannot be persisted.
- Issue: No return data is obtained after calling the external interface, or the returned fields are empty. Cause: The
Authorizationauthentication header is not configured correctly, or the request parameters do not match the field requirements of the target system, resulting in the interface returning a 401 or 404 status code. - Issue: A timeout error occurs after the interface is called, or the returned data format does not match expectations. Cause: A reasonable timeout period is not set, or the structured document format requirements of the target system are not adapted, resulting in parsing failure.
How to confirm the configuration is correct
- Initiate a single test request, check whether the returned response data includes core fields such as sampling number and inspection results, and whether the field format matches the local document definition.
- View the interface call log, confirm that the
Authorizationheader is correctly carried, and there are no authentication-related errors. - Simulate a batch pull request, check whether the interface call frequency meets the restriction requirements of the target system.
- Verify that the request body editing function can be saved and sent normally, with no format errors.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.